audonnx deploys machine learning models stored in ONNX format.
Machine learning models can be trained in a variety of frameworks, e.g. scikit-learn, TensorFlow, Torch. To be independent of the training framework and its version models can be exported in ONNX format, which enables you to deploy and combine them easily.
audonnx allows you to name inputs and outputs of your model, and automatically loads the correct feature extraction from a YAML file stored with your model.
Have a look at the installation and usage instructions.
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Release files for audonnx 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| audonnx-1.0.1.tar.gz | 305.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| audonnx-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 321.1 kB
Release files / audonnx-1.0.1.tar.gz
| Download URL | audonnx-1.0.1.tar.gz |
|---|---|
| Size | 305.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / audonnx-1.0.1-py3-none-any.whl
| Download URL | audonnx-1.0.1-py3-none-any.whl |
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| Size | 16.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
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